{{% hassett_navigation current=top %}} A set of notes on [Hassett and Stewart, 2009](https://archive.org/details/probabilityforri0000hass). [Other texts](/pages/probability-textbooks). [The syllabus](https://www.soa.org/493d4d/globalassets/assets/files/edu/2025/2025-07-exam-p-syllabus.pdf). [TOC] Syllabus ================ + [Chapter 1](chapter-1). Probability: a tool for risk management. pp. 1–7 Who uses probability; an example from insurance; probability and statistics; some history; computing technology. + [Chapter 2](chapter-2). Counting for probability. pp. 7–45 What is probability? The language; notation; set identities; counting. + [Chapter 3](chapter-3). Elements of probability. pp. 45–83 Counting equally-likely and not-equally-likely outcomes; conditional probabilities; independence; Bayes's Theorem. + [Chapter 4](chapter-4). Discrete random variables. pp. 83–113 Random variables; their probability functions; central tendencies and expected values; variance and standard deviation; population and sample statistics. + [Chapter 5](chapter-5). Commonly used discrete distributions. pp113–149 Binomial, hypergeometric, Poisson, geometric, negative-binomial distributions. + [Chapter 6](chapter-6). Applications for discrete random variables. pp 149–175. Sections 6.1, 6.2.1 only: Functions of random variables and their expectations; moments of a random variable. + [Chapter 7](chapter-7). Continuous random variables. pp. 175–195 Defining continuous random variables; mode, median, and percentiles; mean and variance. + [Chapter 8](chapter-8). Commonly-used continuous distributions. pp. 195–255 Uniform, exponential, gamma, normal, log-normal, beta distributions; fitting theoretical distributions to real problems. excluding 8.6, 8.7, Pareto and Weibull + [Chapter 9](chapter-9). Applications for continuous random variables. pp. 255–287 Expected values; mixed distributions. excluding 9.2, 9.3, 9.4, 9.6 + [Chapter 10](chapter-10). Multivariate distributions. pp. 287–321. Joint distributions for discrete variables; conditional distributions (discrete); independence (discrete). Multinomial distribution. excluding 10.2, 10.3.2, 10.3.3 continuous, 10.4.2 + [Chapter 11](chapter-11). Applying multivariate distributions. pp. 321–373 Distributions of functions of two random variables; expected values; sums of more than two variables; double expectation theorems; compound Poisson distribution. excluding 11.1.4 11.2.3 continuous, 11.2.5 continuous, 11.2.8, 11.3